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Using Machine Vision

Optical Character Recognition (OCR)

Three Ways to Enhance

Pharmaceutical Packaging Lines

Technology White Paper

Technology White Paper

Three Ways to Enhance Pharmaceutical Packaging Line

Performance with Machine Vision OCR

This white paper focuses on optical character recognition (OCR) and its extensive use in pharmaceutical packaging for compliance with date

and lot tracking regulations. Machine vision OCR helps manufacturers adhere to these mandates in an effi cient and cost-effective manner,

and can also improve line performance. Three common applications are described here:

- Ensuring code presence and verifi cation of readability

- Tracking products throughout the supply chain

- Matching product labels to contents

Microscan Systems, Inc.

1 www.microscan.com

What Is OCR?

OCR, or optical character recognition, is a vision system tool that is widely

used in the pharmaceutical packaging industry. Like barcode technology,

OCR is a data capture methodology. Its primary advantage is that it encodes

information in a format that is both machine-readable and human-readable,

while barcodes and 2D symbols are only machine-readable. OCR turns printed

text characters from a digital image into a string of characters that can be de-

coded (read) by the system, and then moved through subsequent steps in the

production process as de ned by the control software. The simplest and most

reliable method for optical character recognition relies on speci c OCR fonts

and templates that are designed for these applications. However, machine

vision’s powerful functionality incorporates teachable OCR systems that can

be trained to recognize characters in a user-de ned font – a useful feature

given the wide array of available printing technologies and the range of printed

characters produced by them.

The Need for OCR

Lot codes, batch codes, and expiration dates have become necessary in the pharmaceutical industry, which has stringent labeling

requirements to help ensure consumer safety and to prevent product diversion and counterfeiting. The capability of machine vision to

read these text strings reliably, at high speeds, has become indispensible in today’s manufacturing environment. OCR and subsequent

data retrieval help to ensure the smooth  ow of information throughout the manufacturing and distribution process.

Three Common Uses of OCR in Pharmaceutical Packaging

Many manufacturers initially implement an OCR system for the sole purpose of compliance with standards, but they quickly realize

the many advantages that machine vision can bring to their packaging operations. Automated vision systems increase throughput and

eliminate human error to achieve optimal line performance. OCR not only helps to facilitate (and better yet, prevent) product recalls,

but saves cost by reducing scrapped product and minimizing downtime.

With multiple proven bene ts, quality monitoring by vision technology is used for a wide range of applications. Common uses of

machine vision OCR include verifying the presence of marked characters on products or packaging, reading date/lot codes for product

traceability, and matching labels to products.

A crisp OCR font (left) is the simplest and most reliable

method for decoding, while more challenging marks such as

the inkjet mark on the bottom of the bottle (right) can be read

using teachable OCR systems.

Technology White Paper

1.

OCR ensures code presence and readability - before products exit the factory

One of the most basic tasks of machine vision is to verify that required text strings make it onto the

product or packaging. For example, inkjet printers are commonly used for marking date codes, batch

codes and expiration dates in many packaging applications, due to their ability to print variable

information at very high speed. However, print quality can degrade over the course of process runs,

resulting in inconsistent codes or no code at all. Without a system in place to con rm the

presence of the code, a printing fault - such as a clogged nozzle, interference from debris, or

depleted ink - may affect print quality, and this error could go unnoticed until later in the process.

This results in increased downtime, costly re-runs or worse: if the product makes it out of the factory

without a required code, it will need to be scrapped or recalled.

While OCR will read a code to determine its presence, another vision tool, optical character

verifi cation, or OCV, may be recommended for applications that require con rmation that a code will

be readable after it leaves the plant. OCV-based inspection is most often used to verify that the

printed codes will be of suf ciently high quality to be legible throughout the supply chain in the event

of a product recall – of particular concern in the pharmaceutical industry.

Absent or unreadable codes are unacceptable in this highly regulated industry. Machine vision

provides manufacturers with the peace of mind that their products are properly marked before they

make their way into the supply chain.

2. OCR tracks products throughout the supply chain

Traceability through every step of the manufacturing process is critical in any industry where

manufacturers are required to comply with safety and anti-counterfeiting regulations. Global anti-

terrorism measures have recently placed even more priority on product traceability. Items must be

locatable at any given time within the supply chain, with clear data documenting where they

originated and where they have been.

While product tracking is often considered a barcoding application, lot codes, batch codes,

expiration dates and serial numbers can be read with OCR to follow a product through all phases of

the packaging process - from the primary product label or packaging, to carton packing, to

palletizing operations. An OCR application can be programmed to compare the actual text with an

expected string, as de ned in the database, and  ag any missing or out-of-sequence serial

numbers. Barcodes and OCR are frequently used together to achieve maximum reliability of the

data collection process.

Reliable product tracking and data management of the production and distribution process is

crucial in the event of a safety recall after the product has left the factory, and also plays an

important role in preventing diversion of goods to so-called “gray market” vendors.

3. OCR matches labels to products

Manufacturers must accurately state the contents of an item on its label or packaging, or face

severe consequences, such as government-imposed penalties, costly recalls, and diminished brand

perception. One of the most common reasons for product recalls - mislabeling - has serious

implications for both manufacturers and consumers, ranging from customer dissatisfaction to safety

risks.

OCR can help to ensure that otherwise unmarked products receive the correct label during the

labeling process. Frequently, when products are placed in containers, they are done so with no

labels, as “bright stock”. The only indication of what is inside the bottle or container is a text string

or barcode that identi es the contents. When it is time to put a label on the bottle, the system

reads the characters on it to determine which product is inside the container, then instructs the sys-

tem to apply the correct label to that product. OCR is highly effective in applications where multiple

character strings, such as sequential numbers, are presented to the system. In applications where

all of the contents are expected to be the same, optical character veri cation (OCV) may be recom-

mended; in these cases, the vision system does not read the characters, but instead veri es that

they match an expected string.

Machine vision automation eliminates human error due to fatigue and distraction, resulting in

improved accuracy and increased throughput.

Batch codes track

pharmaceuticals throughout the

supply chain, facilitating the recall

process and preventing product

diversion.

2 www.microscan.com

OCR characters can be used to

make sure that the correct label is

put on the container.

OCR can be used to confi rm that

every product is marked with the

appropriate text string before

exiting the factory.

Technology White Paper

3©2011 Microscan Systems, Inc. 06/11

Conclusion

OCR is used in a wide range of pharmaceutical packaging applications for reliable process control, helping manufacturers meet label-

ing requirements, protecting them from product recalls, and ensuring consumer safety. It is one of a number of valuable tools that

machine vision can provide its users. In addition, vision systems can be used to align labels, inspect  ll levels, read 1D/2D barcodes,

and countless other tasks. Manufacturers are realizing that machine vision is not just a necessary overhead expense for meeting

requirements; these systems quickly pay for themselves through increased yield and productivity, improved product quality, and en-

hanced brand perception.

OCR solutions from Microscan

Microscan has more than twenty years of experience providing OCR solutions

to a broad range of industries. A global technology leader with extensive

solutions for ID tracking, traceability and inspection, Microscan’s line of 1D

and 2D barcode readers, machine vision systems, and machine vision

lighting is backed by one of the world’s most robust patent portfolios and

years of proven performance in the  eld. Microscan offers a number of

products for OCR, including smart cameras, machine vision software, and 2D

imagers with OCR decoding capability.

Supported by a highly skilled global integrator network, Microscan products

are known and trusted by customers worldwide for their high precision and

reliability in industrial automation and control applications, with solutions

ranging from basic barcode reading to complex machine vision inspection,

gauging, and measurement.

More information on Microscan is available at www.microscan.com.

www.microscan.com

North America (Corporate Headquarters)

Email: info@microscan.com

Europe

Email: info@microscan.nl

Asia Pacifi c

Email: asia@microscan.com